Using App Store Search Autocomplete for Keyword Research

Why autocomplete is valuable

Search suggestions are generated from what people actually search, so they reflect real demand in the user's own words. They often reveal long-tail phrases, synonyms, and use cases that brainstorming misses, such as specific features, audiences, or problems.

Suggestions are free, available in every storefront, and update as trends change. They complement ASO tools, which estimate popularity, by showing the exact phrasing users type. Our ASO keyword research framework uses suggestions as an early discovery step.

The basic method

Open the App Store or Google Play in the target storefront and type a core term, such as budget, slowly. Note the suggestions that appear. Then type the term followed by a space and each letter of the alphabet, such as budget a, budget b, and so on, to surface more suggestions. This is sometimes called alphabet soup.

Repeat with letters before the term, such as a budget, and with related core terms. Record every relevant suggestion in a spreadsheet grouped by theme: features, audiences, use cases, and occasions.

Use modifiers

Add common modifiers to core terms: free, offline, for kids, for couples, simple, tracker, planner, app, game, and so on. Modifiers reveal how users narrow their searches and which audiences or features matter.

For games, combine genre, mechanic, theme, and mood terms, as described in our game keyword research guide.

Storefronts and languages

Suggestions differ by country and language. Check suggestions in each priority storefront, ideally with a device or account set to that region and language. Translation of English suggestions rarely matches local queries.

Our app store localization strategy explains researching locally, and market guides such as ASO for Japan or ASO for Germany cover language-specific patterns.

Personalization and bias

Suggestions can be influenced by your search history and device. Use a clean device or account where possible, and compare results across devices. Treat suggestions as indicators of demand rather than ranked volume.

Suggestions also reflect trends and brand searches. A competitor's brand appearing in suggestions shows demand, but do not use trademarked names in your metadata.

Validate with data

Once you have a list of suggestions, check popularity using Apple Ads popularity scores and ASO tool estimates, and evaluate relevance and competition. Our keyword popularity and difficulty scores guide explains how to interpret these signals.

Store analytics show which search terms already bring visitors. Play Console lists search terms for your app, and Apple Ads search terms reports show converting queries.

Turn ideas into metadata

Prioritize relevant phrases and assign them to metadata fields. On the App Store, use the name, subtitle, and keyword field, avoiding repetition. On Google Play, use natural language in the title, short description, and full description.

Our guides to the App Store keyword field, App Store subtitle formulas, and Google Play long description writing explain placement.

Use suggestions for creative too

Suggestions reveal the language and benefits users care about, which can inform screenshot captions and promotional text. If users search for budget for couples, a caption about shared budgets may resonate.

Our screenshot caption copywriting guide explains turning user language into persuasive captions.

Repeat regularly

Suggestions change with seasons, trends, and new competitors. Repeat research quarterly, before major updates, and before seasonal peaks. New suggestions can reveal emerging opportunities early.

Our seasonal ASO calendar helps schedule research before key periods.

Turning suggestions into a keyword map

A raw list of suggestions becomes useful once it is organized. Group phrases by theme, note which storefront and language each came from, and record whether your app genuinely supports the need behind it. Phrases that combine a core term with a feature or audience, such as budget app for couples, often become strong long-tail targets.

Add popularity estimates and your current rank for each phrase, then mark which field it will live in. This map becomes the source of truth for metadata decisions and future tests, as described in our keyword cannibalization guide, which explains keeping fields from competing with each other.

Common autocomplete research mistakes

Researching only in one storefront or language misses local queries. Using suggestions without validating popularity and relevance leads to weak keywords. Copying competitor brand suggestions into metadata risks rejection.

Teams also research once and never repeat, missing new trends.

A worked example: a habit tracker

A habit tracker team types habit and habit tracker with letter combinations in the US App Store. Suggestions include habit tracker for adhd, habit tracker widget, and daily routine planner. The team validates popularity, finds habit tracker widget relevant with moderate popularity, and adds widget to the keyword field.

It also tests a screenshot caption about home screen widgets. Rankings for habit tracker widget rise into the top ten, and the new caption improves conversion.

How to do it, step by step

1. List core termsWrite the main terms that describe your app.
2. Expand with letters and modifiersType core terms with each letter and common modifiers, recording suggestions.
3. Repeat per storefront and languageResearch in each priority market with local settings.
4. Validate and prioritizeCheck popularity, relevance, and competition before using terms.
5. Apply to metadata and creativeAssign phrases to fields and use user language in captions.

Before and after examples

Illustrative examples written for a generic app in this category, not client results. Swap in your own product, audience, and data.

Action plan

1. Use suggestions for discovery
2. Expand with letters and modifiers
3. Research every storefront and language
4. Validate with popularity data
5. Use user language in creative
6. Repeat research quarterly

Metrics to monitor

• New relevant keywords found
• Rankings for suggestion-derived terms
• Search impressions
• Conversion rate from search
• Caption test results

Record the baseline, release date, audience, markets, and external changes before interpreting movement. Rankings and conversion are useful signals, but a decision is stronger when activation, retention, and business value confirm that the page attracted the right users.

Frequently asked questions

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